Ireneusz Bachanowicz
2763b40b60
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- Simplified the FastAPI application structure and improved error handling with middleware. - Introduced a retry decorator for asynchronous functions to enhance reliability. - Modularized the LLM initialization and prompt loading into separate functions for better maintainability. - Updated Pydantic models for Jira webhook payload and analysis flags to ensure proper validation and structure. - Implemented a structured logging configuration for better traceability and debugging. - Added comprehensive unit tests for prompt loading, response validation, and webhook handling. - Established a CI/CD pipeline with GitHub Actions for automated testing and coverage reporting. - Enhanced the prompt template for LLM analysis to include specific instructions for handling escalations.
102 lines
3.3 KiB
Python
102 lines
3.3 KiB
Python
from fastapi import FastAPI, Request, HTTPException
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from pydantic import BaseModel
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from fastapi.responses import JSONResponse
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from loguru import logger
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import uuid
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import sys
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from typing import Optional
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from datetime import datetime
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import asyncio
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from functools import wraps
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from config import settings
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from webhooks.handlers import JiraWebhookHandler
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from llm.models import JiraWebhookPayload
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from logging_config import configure_logging
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try:
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app = FastAPI()
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logger.info("FastAPI application initialized")
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except Exception as e:
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logger.error(f"Error initializing FastAPI: {str(e)}")
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raise
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# Initialize logging
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configure_logging(log_level=settings.log.level)
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def retry(max_retries: int = 3, delay: float = 1.0):
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"""Decorator for retrying failed operations"""
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def decorator(func):
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@wraps(func)
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async def wrapper(*args, **kwargs):
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last_error = None
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for attempt in range(max_retries):
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try:
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return await func(*args, **kwargs)
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except Exception as e:
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last_error = e
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logger.warning(f"Attempt {attempt + 1} failed: {str(e)}")
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if attempt < max_retries - 1:
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await asyncio.sleep(delay * (attempt + 1))
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raise last_error
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return wrapper
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return decorator
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class ErrorResponse(BaseModel):
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error_id: str
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timestamp: str
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status_code: int
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message: str
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details: Optional[str] = None
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@app.middleware("http")
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async def error_handling_middleware(request: Request, call_next):
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request_id = str(uuid.uuid4())
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logger.bind(request_id=request_id).info(f"Request started: {request.method} {request.url}")
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try:
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response = await call_next(request)
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return response
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except HTTPException as e:
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logger.error(f"HTTP Error: {e.status_code} - {e.detail}")
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error_response = ErrorResponse(
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error_id=request_id,
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timestamp=datetime.utcnow().isoformat(),
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status_code=e.status_code,
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message=e.detail,
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details=str(e)
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)
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return JSONResponse(status_code=e.status_code, content=error_response.model_dump())
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except Exception as e:
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logger.error(f"Unexpected error: {str(e)}")
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error_response = ErrorResponse(
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error_id=request_id,
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timestamp=datetime.utcnow().isoformat(),
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status_code=500,
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message="Internal Server Error",
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details=str(e)
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)
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return JSONResponse(status_code=500, content=error_response.model_dump())
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webhook_handler = JiraWebhookHandler()
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@app.post("/jira-webhook")
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async def jira_webhook_handler(payload: JiraWebhookPayload):
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return await webhook_handler.handle_webhook(payload)
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@app.post("/test-llm")
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async def test_llm():
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"""Test endpoint for LLM integration"""
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test_payload = JiraWebhookPayload(
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issueKey="TEST-123",
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summary="Test issue",
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description="This is a test issue for LLM integration",
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comment="Testing OpenAI integration with Langfuse",
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labels=["test"],
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status="Open",
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assignee="Tester",
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updated="2025-07-04T21:40:00Z"
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)
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return await webhook_handler.handle_webhook(test_payload)
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# To run this:
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# 1. Start FastAPI: uvicorn main:app --host 0.0.0.0 --port 8000 --reload |